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Fast implementation of the Niblack binarization algorithm for microscope image segmentation

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Pattern Recognition and Image Analysis Aims and scope Submit manuscript

Abstract

A fast way to implement the Niblack binarization algorithm is described. It uses not only the integral image for the local mean values calculation, but also the second order integral image for the local variance calculation. Following the proposed approach the time of segmentation has been significantly reduced providing the possibility of its use in practice. The generalization of integral image representation, called ‘k-order integral image’ could be used for fast calculation of higher order local statistics. An example of algorithm for the segmentation of cells and Chlamydial inclusions on microscope images, containing the steps for color deconvolution and fast adaptive local binarization is presented.

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Authors and Affiliations

  1. Chair for Biomedical Technical Systems, Faculty of Biomedical Technique, Bauman Moscow State Technical University, Moscow, Russia

    O. A. Samorodova & A. V. Samorodov

Authors
  1. O. A. Samorodova
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  2. A. V. Samorodov
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Corresponding author

Correspondence to O. A. Samorodova.

Additional information

This paper uses the materials of the report submitted at the 9th Open German-Russian Workshop on Pattern Recognition and Image Understanding, held in Koblenz, December 1–5, 2014 (OGRW-9-2014).

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Ol’ga Aleksandrovna Samorodova. Born. 1986. Graduated from Bauman Moscow State Technical University in 2009. Received candidate (PhD) degree in engineering sciences at Bauman Moscow State Technical University in 2013. Associate professor, Chair for Biomedical Technical Systems, Bauman Moscow State Technical University. Fields of research priorities: automated microscopy of biomedical preparations, biomedical image processing and analysis. biomedical statistics, computer-aided decision-making systems in medicine. Author of 60 scientific publications, including 13 journal papers.

Andrei Vladimorovich Samorodov. Born 1975. Graduated from Bauman Moscow State Technical University in 1999. Received candidate (PhD) degree in engineering sciences at Bauman Moscow State Technical University in 2002. Head of the Chair for Biomedical Technical Systems, Bauman Moscow State Technical University. Fields of research priorities: methods and algorithms of pattern recognition and multiclassification, automated microscopy of biomedical preparations.computer-aided decisionmaking systems in medicine, methods and technique for biomedical images and signals recognition Author of more than 200 scientific publications (including 1 collective monograph and more than 30 journal papers).

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Samorodova, O.A., Samorodov, A.V. Fast implementation of the Niblack binarization algorithm for microscope image segmentation. Pattern Recognit. Image Anal. 26, 548–551 (2016). https://doi.org/10.1134/S1054661816030020

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  • DOI: https://doi.org/10.1134/S1054661816030020

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